Unplugged: Raptors consultant Alex Rucker on advanced stats, Part 1

National Post basketball reporter Eric Koreen sat down with Toronto Raptors analytics consultant — technically, he is on contract work with the Raptors, although on a full-time basis — Alex Rucker earlier in the week for a wide-ranging interview. In Part One of the interview, Rucker discusses how he got his job, the Raptors’ standing in the world of analytics and how far advanced statistics have come in the last few years. The interview has been edited for length at various points.

Q: How did you become involved with basketball analytics?
“I realized probably in my senior year of high school that my future in professional basketball was not as likely as I once hoped it would be. I played a lot of sports. I was a big baseball fan at the time. The notion of understanding something more thoroughly through an objective, unbiased approach was very, very appealing to me. When I got to my first year of college at the University of Western Ontario, that is when I first got into basketball analytics, working with the basketball program there in the early ’90s when basketball stats were at a very nascent stage … It’s an odd road. I did two years at Western in financial and economic studies. Then I transferred back to Vancouver through a connection with [former Raptors coach and current Canadian national team coach] Jay Triano, interestingly, who I’d worked with at Simon Fraser. I helped him run some camps. So I was at the [University of British Columbia] and worked with the Vancouver Grizzlies and their stats team. I did that for three years while completing my degree in commerce. When I left the Grizzlies, I went to law school at Notre Dame. I did a three-year degree. Neither one of those necessarily equals statistics. The business stuff was a lot of financial, economic modeling. The law degree was much more useful in critical thinking and, frankly, learning to read and write. It turns out those are very valuable skills.”

Between 2001 and 2012, Rucker served in the United States Navy as an officer, aviator and professor.
“During that time, I was heavily involved on a personal level with basketball statistics or what is commonly referred to as advanced basketball analysis, or analytics. That involved into a chance meeting with Jay, which turned into this.”

Q: When did contact with Jay happen, and how has your role with the team progressed?
“The initial Raptor contact with Jay would have been in July 2009 at Summer League. I had been attending Summer League [in Las Vegas] for years as a basketball fan. The chance to go there and watch eight hours a day was manna from heaven. For me, that’s phenomenal, a great way to spend a day. Three years ago, I ran into Jay, and he had just completed his interim duty and had just been named head coach. We had a good chat. I said to him, ‘There’s this emerging field of analytics that could be helpful to you.’ He said he was aware of it and knew several teams that were really into it. It was something he and [Raptors president and general manager Bryan Colangelo] were talking about wanting to expand the Raptors’ involvement in. Bryan is very innovative and forward thinking, if you look across all of the GMs … The combination of a more progressive GM and a young coach that wanted to progress and grow and take advantage of all of the tools out there [was helpful to me]. I was, in a sense, that tool.”

Q: At that point, were the Raptors behind the curve? Or were most teams just not interested in analytics?
“My sense is that most teams were somewhat involved with statistical analysis at very different levels. There were teams that were very invested at that point. It’s public which teams were ahead of the curve back then, whether it was Dallas or Houston … I think it would be false to say the Raptors were behind the curve in that they were below average. I think it’s more correct to say that there were 20-plus teams that weren’t heavily invested in it at that point. The Raptors were probably ahead of that group, but not in the way-ahead-of-the-curve groups that had invested a lot in analytics at that point.”

Q: Were there any people in baseball or basketball that you read that you looked up to?
“On the baseball side, Bill James is the face of sabermetrics, baseball analytics. Throughout the ’80s, there was fascinating work done by a large number of people, such that once the internet came online, all of the information was out there. The code was pretty much cracked in baseball by the late ’80s, early ’90s. As a young person interested in analytics, it was a phenomenal post-graduate education in sports statistics. In basketball, I read Dean Oliver’s book [Basketball On Paper: Rules And Tools For Performance Analysis]. Other than that, there isn’t a ton of good basketball analytics that are in the public sphere. Oliver’s book was a good foundation of a new way to look at the game, a way to quantify things that had previously been in the realm of intuition, observation, common wisdom.”

Related

Q: How far have basketball analytics come in the NBA over the last three to five years?
“There’s clearly been a significant increase in that across the league … There is a very clear sense that the majority of teams are using advanced statistics to some level or another. Again, they are pretty much all, including us, proprietary about what they do. Based on personnel hiring or online job advertisements, you can get a sense of where they are going by who they’ve hired and what they’ve taken advantage of. I think at this point, it’s very clear that the majority if not the super majority of NBA teams have full-time analytics support. There is obviously going to be a great range of quality of support, and also a great range of how ingrained they are in the organizations. There are analytics guys that work with teams but I know by talking from them that their impact is at a very low level.”

Q: How important are analytics in basketball? How much should top basketball executives listen to you?
“The bottom-line answer to me is that having an unbiased, objective way of assessing players is fundamental to making decisions on transactions or [giving out] contracts. In any discipline, if you can get it down to something unbiased at a decision point, I think that’s fundamentally correct. When a general manager makes a decision about a player, you do want that to rest to a certain extent on analytics. I will say, however, that I have never once subscribed to the notion that you can ‘build a team by the numbers.’ It’s still one factor of several. Analytics should be a big part of making a decision, but not the only part. There are other things that matter a great deal in terms of building a team that you can get at elements of analytically but, at the end of the day, there are still some qualitative things that are critically important. You can’t capture them, no matter how many cool, expensive cameras I have taking pictures.”

Q: Is there a specific slant to what the Raptors do analytically?
“The two core pieces of analytically ideology are: one, what data do you have, and two, how do you use it or what are you looking to find [from] it? With respect to the data, I think there are massive discrepancies between NBA teams. And we are frankly at the leading edge of that. We’ve invested heavily in the SportVu camera system. We have a robust data collection process, whether it is coaches, interns or other people. I think that we are at the leading edge in terms of data that we hold. But I think that edge is a temporary one. I think it’s a matter of time before every team has the cameras and has the volume of data that we enjoy … I think that our team has some fairly clear identities. [Raptors coach Dwane Casey] has set a clear culture and points of emphasis as far as what we’re doing to do as a team. I’m not going to go anywhere near [mentioning] specific metrics or processes. But I think our focus has shifted over the last three years. We’re focused on what kind of team does Bryan want to assemble, and what kind of performance does Dwane want on the court …”

Q: Defence is seen as a weakness in public analytics. Do you think that is the case?
“Oh yes. There’s a fairly low level of correlation between something like steals per game and a point guard’s defensive abilities. Sometimes there’s a good alignment. Sometimes a guy that gets a lot of steals is a horrible defender … Looking at blocks gets you closer, but not really. There are plenty of guys that get two or three blocks per game that are really poor defenders. It is true that people in the public are at an extreme disadvantage because the public data isn’t there. It’s not like baseball where all data is there for everybody. This is a world where what you guys have at the end of the day is boxscore data and a play by play. That just doesn’t get you anywhere near a good answer on defence.”

Q: A common misconception about Moneyball was that it was about valuing on-base percentage. Instead, it was about valuing what was undervalued at the time in baseball at large. Are there any areas in basketball that are routinely undervalued in free agency?
“First of all, you’re absolutely correct. If Moneyball were the messenger in this analytic resurgence in baseball, it is absolutely correct that on-base percentage had nothing to do with it except that it was the thing that was being exploited. There was league-wide market inefficiency where 29 or whatever number of the GMs critically undervalued this valuable area of production. In our world, the trite answer would be defence is the one thing that is chronically [undervalued]. And that is because the data is hard to get, lots of teams don’t have it, and the ones that do are [not always] using it optimally.”

Q: Has that changed at all?
“I would say that the market has gotten more efficient over the last five years. It’s clear that there is a better appreciation of, a better evaluation of some of the inefficiencies I see when going through this morass of data. That’s one example. There are other examples where there are things I think are valued [incorrectly]. But defence is the big one just because it’s so difficult to assess.”

Q: Short of lacing NBA arenas with cameras, watching every game or getting a graduate degree, what can the average fan do to become more educated, whether it is through public stats or a taking different look at the game?
“There are actually some really good analysts and bloggers and work being done in the public sphere. You’ve got a core of mainstream advanced stats, whether it’s [player efficiency rating] or true shooting percentage or usage rates and offensive ratings, some of [ESPN analyst John] Hollinger’s stuff, some of the stuff on 82games.com, Roland Beech’s site, and he now works for the Mavericks: All of these things are valuable. They all tell you something. As a student of the game, what I would encourage you to do is look at those things as reference points, try to understand what they mean. They all have limitations. But you don’t get to the limitations unless you try to understand them in the first place. PER, for instance, is a very mainstream advanced stat. It’s quite valuable. It’s a really good way for an average person in the public to get an overall sense of a guy’s offensive contributions. If I’m an average fan, I probably spend a lot more time on Basketball-Reference.com, which has an advanced metrics set of data that’s got most of the mainstream things there. Those tell you a lot more than you’re going to get from per-game data.”